Generation of antibodies for therapeutic uses typically involves a lead discovery phase followed by an optimization process (Almagro and Strohl, Antibody Engineering: Humanization, Affinity Maturation and Selection Methods. 307-327. In: Therapeutic Monoclonal Antibodies: From Bench to Clinic. Ed. Zhiqiang An. John Wiley & Sons, Inc. 2009). The platforms currently available for lead discovery include hybridoma technology (Kohler et al., Nature, 256:495-7, 1975), in vitro display-based technologies (Hoogenboom, Nat Biotechnol, 23:1105-16, 2005), and transgenic mice expressing human immunoglobulins (Lonberg et al., Nature 368:856-9, 1994). In a typical antibody lead development campaign, optimization of initial discovery hits is typically required to improve affinity, solubility and stability.
A number of strategies to increase affinity of antibodies have been reported, including random (Groves et al., J Immunol Methods, 313:129-39, 2006) and site-directed mutagenesis (SDM) methods (Barbas et al., Proc Natl Acad Sci USA, 91:3809-13, 1994), combined with for example in vitro display-based technologies such as phage or ribosome display to generate libraries of variants for subsequent screens (Almagro and Strohl, Antibody Engineering: Humanization, Affinity Maturation and Selection Methods. 307-327. In: Therapeutic Monoclonal Antibodies: From Bench to Clinic. Ed. Zhiqiang An. John Wiley & Sons, Inc. 2009). However, only a limited number of residues can be diversified as the size of the libraries increases exponentially for every diversified residue. For example, a library built on the common NNK diversification scheme, which introduces 32 codons in every position, grows by 32n for every n number of residues. Phage libraries are normally limited to a size of 109-1010 members, indicating that only 6-7 residues can be diversified if full sequence coverage is to be achieved in the library.
Strategies for diversification to attain maximal sequence coverage include generation of antibody libraries by targeting solvent accessible antibody residues (US2005/0266000), or targeting residues based on sequence comparisons (WO2006/014498). More focused strategies include diversification of residues at HCDR3 (Schier et al., J Mol Biol 263:551-67, 2006) since it is well known that this region of the antigen-binding site is often critical to define the specificity and affinity of antibodies. The diversity of the libraries has been designed in some cases to mirror the composition and frequency of amino acids in natural antibodies (Cobaugh et al., J Mol Biol, 378:622-33, 2008; Knappik et al., J Mol Biol, 296:57-86, 2000; Lee et al., J Mol Biol, 340:1073-93, 2004; Hoet et al., Nature
Biotechnol, 23:344-8, 2005). Also, a combinations of a few amino acids (Fellouse et al., Proc Natl Acad Sci USA, 101:12467-72, 2004; Sidhu and Fellouse, Nature Chemical Biology, 2:682-8, 2006), or a binary code restricted to tyrosine and serine (Fellouse et al., J Mol Biol, 348:1153-62, 2005) have been used.
Developing therapeutic antibodies with higher affinity can have a direct impact on efficacy as well as on dosage and hence, potential immunogenicity and production costs. Thus, there is a need for improved methods for affinity maturing antibodies.